Traitement des signaux EMG et son application pour commander un exosquelette

Le vieillissement de la population dans notre société moderne va entraîner de nouveaux besoins pour l’assistance aux personnes âgées et pour la réhabilitation. Les exosquelettes sont une piste de recherche prenant de plus en plus d’importance pour répondre à ces nouveaux challenges. Deux de ces challenges sont, la réalisation d’un contrôle naturel pour l’utilisateur et la sécurité. Cette maîtrise cherche à répondre à ces deux problématiques. Nous avons donc développé un outil de travail informatique utilisant les décharges électriques produites par les neurones moteurs pour contracter les muscles et un modèle des os et des muscles du bras. Cet outil utilise la librairie informatique ROS et OpenSim. Elle permet de connaître la force et le mouvement développés par le coude. De plus, un autre outil informatique a été développé pour optimiser le modèle des os et des muscles du bras pour le personnaliser à l’utilisateur pour un meilleur résultat. Une carte d’acquisition utilisant des électrodes de surface pouvant être reliées avec un ordinateur par USB et compatible avec ROS a été développée. Pour tester les algorithmes développés, un exosquelette pour le coude utilisant un actionneur compliant et contrôlé en force a été conçu. Pour compenser le poids de l’exosquelette et l’effet d’amortissement passif de l’actionneur, une compensation de gravité dynamique a été développée. Finalement, des expérimentations ont été menées sur l’efficacité de l’optimisation du modèle et sur l’exosquelette avec les différents algorithmes

Robust simultaneous myoelectric control of multiple degrees of freedom in wrist-hand prostheses by real-time neuromusculoskeletal modeling

Objectives: Robotic prosthetic limbs promise to replace mechanical function of lost biological extremities and restore amputees' capacity of moving and interacting with the environment. Despite recent advances in biocompatible electrodes, surgical procedures, and mechatronics, the impact of current solutions is hampered by the lack of intuitive and robust man-machine interfaces. Approach: Based on authors' developments, this work presents a biomimetic interface that synthetizes the musculoskeletal function of an individual's phantom limb as controlled by neural surrogates, i.e. electromyography-derived neural activations. With respect to current approaches based on machine learning, our method employs explicit representations of the musculoskeletal system to reduce the space of feasible solutions in the translation of electromyograms into prosthesis control commands. Electromyograms are mapped onto mechanical forces that belong to a subspace contained within the broader operational space of an individual's musculoskeletal system. Results: Our results show that this constraint makes the approach applicable to real-world scenarios and robust to movement artefacts. This stems from the fact that any control command must always exist within the musculoskeletal model operational space and be therefore physiologically plausible. The approach was effective both on intact-limbed individuals and a transradial amputee displaying robust online control of multi-functional prostheses across a large repertoire of challenging tasks. Significance: The development and translation of man-machine interfaces that account for an individual's neuromusculoskeletal system creates unprecedented opportunities to understand how disrupted neuro-mechanical processes can be restored or replaced via biomimetic wearable assistive technologies

MyoSim:Fast and physiologically realistic MuJoCo models for musculoskeletal and exoskeletal studies

Owing to the restrictions of live experimentation, musculoskeletal simulation models play a key role in biological motor control studies and investigations. Successful results of which are then tried on live subjects to develop treatments as well as robot aided rehabilitation procedures for addressing neuromusculoskeletal anomalies ranging from limb loss, to tendinitis, from sarcopenia to brain and spinal injuries. Despite its significance, current musculoskeletal models are computationally expensive, and provide limited support for contact-rich interactions which are essential for studying motor behaviors in activities of daily living, during rehabilitation treatments, or in assistive robotic devices. To bridge this gap, this work proposes an automatic pipeline to generate physiologically accurate musculoskeletal, as well as hybrid musculoskeletal-exoskeletal models. Leveraging this pipeline we present MyoSim - a set of computationally efficient (over 2 orders of magnitude faster than state of the art) musculoskeletal models that support fully interactive contact rich simulation. We further extend MyoSim to support additional features that help simulate various real-life changes/diseases, such as muscle fatigue, and sarcopenia. To demonstrate the potential applications, several use cases, including interactive rehabilitation movements, tendon-reaffirmation, and the cosimulation with an exoskeleton, were developed and investigated for physiological correctness. Web-page: https://sites.google.com/view/myosuit

Neuromechanical Model-Based Adaptive Control of Bilateral Ankle Exoskeletons:Biological Joint Torque and Electromyogram Reduction Across Walking Conditions

To enable the broad adoption of wearable robotic exoskeletons in medical and industrial settings, it is crucial they can adaptively support large repertoires of movements. We propose a new human-machine interface to simultaneously drive bilateral ankle exoskeletons during a range of 'unseen' walking conditions and transitions that were not used for establishing the control interface. The proposed approach used person-specific neuromechanical models to estimate biological ankle joint torques in real-time from measured electromyograms (EMGS) and joint angles. We call this 'neuromechanical model-based control' (NMBC). NMBC enabled six individuals to voluntarily control a bilateral ankle exoskeleton across six walking conditions, including all intermediate transitions, i.e., two walking speeds, each performed at three ground elevations. A single subject case-study was carried out on a dexterous locomotion tasks involving moonwalking. NMBC always enabled reducing biological ankle torques, as well as eight ankle muscle EMGs both within (22% torque;12% EMG) and between walking conditions (24% torque; 14% EMG) when compared to non-assisted conditions. Torque and EMG reductions in novel walking conditions indicated that the exoskeleton operated symbiotically, as an exomuscle controlled by the operator.s neuromuscular system. This opens new avenues for the systematic adoption of wearable robots as part of out-of-the-lab medical and occupational settings

Myoelectric model-based control of a bi-lateral robotic ankle exoskeleton during even ground locomotion ^∗

Individuals with neuromuscular injuries may fully benefit from wearable robots if a new class of wearable technologies is devised to assist complex movements seamlessly in everyday tasks. Among the most important tasks are locomotion activities. Current human-machine interfaces (HMI) are challenged in enabling assistance across wide ranges of locomoting tasks. Electromyography (EMG) and computational modelling can be used to establish an interface with the neuromuscular system. We propose an HMI based on EMG-driven musculoskeletal modelling that estimates biological joint torques in real-time and uses a percentage of these to dynamically control exoskeleton-generated torques in a task-independent manner, i.e. no need to classify locomotion modes. Proof of principle results on one subject showed that this approach could reduce EMGs during exoskeleton-assisted even ground locomotion compared to transparent mode (i.e. zero impedance). Importantly, results showed that a substantial portion of the biological ankle joint torque needed to walk was transferred from the human to the exoskeleton. That is, while the total human-exoskeleton ankle joint was always similar between assisted and zero-impedance modes, the ratio between exoskeleton-generated and human-generated torque varied substantially, with human-generated torques being dynamically compensated by the exoskeleton during assisted mode. This is a first step towards natural, continuous assistance in a large variety of movements

Adaptive model-based myoelectric control for a soft wearable arm exosuit:A new generation of wearable robot control

Despite advances in mechatronic design, the widespread adoption of wearable robots for supporting human mobility has been hampered by 1) ergonomic limitations in rigid exoskeletal structures and 2) the lack of human-machine interfaces (HMIs) capable of sensing musculoskeletal states and translating them into robot-control commands. We have developed a framework that combines, for the first time, a model-based HMI with a soft wearable arm exosuit that has the potential to address key limitations in current HMIs and wearable robots. The proposed framework was tested on six healthy subjects who performed elbow rotations across different joint velocities and lifting weights. The results showed that the model-controlled exosuit operated synchronously with biological muscle contraction. Remarkably, the exosuit dynamically modulated mechanical assistance across all investigated loads, thereby displaying adaptive behavior

Traitement des signaux EMG et son application pour commander un exosquelette

Le vieillissement de la population dans notre société moderne va entraîner de nouveaux besoins pour l’assistance aux personnes âgées et pour la réhabilitation. Les exosquelettes sont une piste de recherche prenant de plus en plus d’importance pour répondre à ces nouveaux challenges. Deux de ces challenges sont, la réalisation d’un contrôle naturel pour l’utilisateur et la sécurité. Cette maîtrise cherche à répondre à ces deux problématiques. Nous avons donc développé un outil de travail informatique utilisant les décharges électriques produites par les neurones moteurs pour contracter les muscles et un modèle des os et des muscles du bras. Cet outil utilise la librairie informatique ROS et OpenSim. Elle permet de connaître la force et le mouvement développés par le coude. De plus, un autre outil informatique a été développé pour optimiser le modèle des os et des muscles du bras pour le personnaliser à l’utilisateur pour un meilleur résultat. Une carte d’acquisition utilisant des électrodes de surface pouvant être reliées avec un ordinateur par USB et compatible avec ROS a été développée. Pour tester les algorithmes développés, un exosquelette pour le coude utilisant un actionneur compliant et contrôlé en force a été conçu. Pour compenser le poids de l’exosquelette et l’effet d’amortissement passif de l’actionneur, une compensation de gravité dynamique a été développée. Finalement, des expérimentations ont été menées sur l’efficacité de l’optimisation du modèle et sur l’exosquelette avec les différents algorithmes

Robust Simultaneous Myoelectric Control of Multiple Degrees of Freedom in Wrist-Hand Prostheses by Real-Time Neuromusculoskeletal Modeling

Objectives: Robotic prosthetic limbs promise to replace mechanical function of lost biological extremities and restore amputees' capacity of moving and interacting with the environment. Despite recent advances in biocompatible electrodes, surgical procedures, and mechatronics, the impact of current solutions is hampered by the lack of intuitive and robust man-machine interfaces. Approach: Based on authors' developments, this work presents a biomimetic interface that synthetizes the musculoskeletal function of an individual's phantom limb as controlled by neural surrogates, i.e. electromyography-derived neural activations. With respect to current approaches based on machine learning, our method employs explicit representations of the musculoskeletal system to reduce the space of feasible solutions in the translation of electromyograms into prosthesis control commands. Electromyograms are mapped onto mechanical forces that belong to a subspace contained within the broader operational space of an individual's musculoskeletal system. Results: Our results show that this constraint makes the approach applicable to real-world scenarios and robust to movement artefacts. This stems from the fact that any control command must always exist within the musculoskeletal model operational space and be therefore physiologically plausible. The approach was effective both on intact-limbed individuals and a transradial amputee displaying robust online control of multi-functional prostheses across a large repertoire of challenging tasks. Significance: The development and translation of man-machine interfaces that account for an individual's neuromusculoskeletal system creates unprecedented opportunities to understand how disrupted neuro-mechanical processes can be restored or replaced via biomimetic wearable assistive technologies